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Proceedings Paper

A comparison of image processing algorithms for thermal nondestructive evaluation
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Paper Abstract

Thermography involves the application of heat to a structure and observation of surface temperature anomalies to reveal subsurface defects. Detection of subsurface defects can be greatly enhanced by the real time capture of a series of thermal images in time and the subsequent analysis of these images using various image processing algorithms. By applying image-processing algorithms, defects not readily observable can be detected and quantitatively characterized. The focus of this work is to investigate several of the numerous data reduction algorithms for thermal nondestructive evaluation by comparing results on a set of test samples. Some new types of data reduction algorithms have been recently developed with advantages such as noise reduction, file size compression, and material property measurements. By comparing various algorithms on factors such as computational speed, simplicity of use, robustness to noise, quantitative information, and optimum defect detection the most efficient algorithm may be chosen based on the user’s needs.

Paper Details

Date Published: 1 April 2003
PDF: 12 pages
Proc. SPIE 5073, Thermosense XXV, (1 April 2003); doi: 10.1117/12.485869
Show Author Affiliations
Joseph N. Zalameda, Army Research Lab. (United States)
Nikolas Rajic, Defence Science and Technology Organisation (Australia)
William P. Winfree, NASA Langley Research Ctr. (United States)


Published in SPIE Proceedings Vol. 5073:
Thermosense XXV
K. Elliott Cramer; Xavier P. Maldague, Editor(s)

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